Here is the full text from PLoS (subscribe to PLoS medicine, btw; all free studies).

Basically, in looking at cases of Ischemic Heart Disease that co-exist with obesity and then factoring out three common gene variants that could have been to blame, there was still a consistent and positive association with BMI and Heart Disease Risk.

Granted the RRs were pretty weak, so its not like Obesity per se is the biggest factor. However, it in and of itself appears to contribute in a way according to this study. The authors hypothesized the increased risk was secondary to common risk factors though, meaning that obesity per se increases risk of diabetes or artherosclerosis or something, which then influences heart disease. This appears to be independent of the three genetic variants they measured though.

Beyond the abstract, at least the editors' summary is worth a read. Cutting and pasting from the section "What do these findings mean?"

These findings support a causal link between increased BMI and IDH risk, although it may be that BMI affects IDH through intermediate factors such as hypertension, dyslipidemia, and diabetes. The findings also show that observational studies into the impact of elevated BMI on IHD risk were consistent with this, but also that the inclusion of genetic data increases the value of observational studies by making it possible to avoid issues such as confounding and reverse causation. Finally, these findings and those of recent, observational studies have important implications for public-health policy because they show that the association between BMI (which is modifiable by lifestyle changes) and IHD is continuous. That is, any increase in BMI increases the risk of IHD; there is no threshold below which a BMI increase has no effect on IDH risk. Thus, public-health policies that aim to reduce BMI by even moderate levels could substantially reduce the occurrence of IDH in populations.

Thoughts?

Tl;Dr: First evidence that I have seen that effectively does claim causation for BMI and heart disease independent of common genetic variants associated with BMI and Heart Disease.

Correlation, as long as it is not due to chance, does in fact imply causation. What it does not do is tell you the direction and structure of the causation.

If A and B are correlated, then the relationship could be

A=>B, or

B=>A, or

C=>A and C=>B

For example being black in the US is correlated with low IQ. This does not necessarily mean blackness causes low IQ. It could be for example that being black and living in Africa caused slavery which caused social deprivation which caused poverty which caused poor diet and education which caused low IQ.

Similarly being female is associated with lower earnings than being male. The common assumption is that this is caused by discrimination against women. But the existence of the correlation merely points to some sort of causal relationship. it doesn't tell you the structure of that relationship.

Perhaps women have different preferences and interests which cause them to choose lower paying jobs that are more pleasant, or to work shorter hours, to take more holidays or to refuse promotions that involve relocation. Or perhaps men are under more pressure to earn more because men are judged by the size of their wallet.

I think you're doing this wrong. What you outlined is generally understood. The problem arises when people prescribe an intervention based on correlation. You could do a study that shows that red cars are faster (perhaps because red cars are more likely to be sports cars, or vice-versa). But however much you run around to show some convoluted causation there, the truth is painting your car red will not make it any faster.

Very true. At the end of the day a statistical model needs to be driven by reason and theory not the other way around. Statistics such as the covariance between variables can help one reject or fail to reject a causal theory. But causal theory is not something we can prove empirically.

I've always thought "correlation doesn't imply causation" was a retarded statement. It doesn't necessitate, or equal, causation. It kind of does imply causation, but the implication could be wrong. Basically whoever came up with "correlation does not imply causation" didn't know the definition of the word imply...

edit: I guess it was "correlation doesn't necessarily imply causation" and then people shortened it by taking out the necessarily and making it an untrue statement. meh, just bugs me

I'd be willing to bet that this expression comes from a more particular meaning of "imply" than is meant in casual speech, such as the definition in formal logical, which if I recall correctly is states by some as: "implication is the validity of the conditional." Meaning of course, than if given a statement if a then b, then there is no way for a to be true and then b to be false. (Not to be confused with equivalence, which is the validity of the biconditional, or as I like to call it two-way-implication.)

Anyhow, I've gotten the feeling that a lot of important people in empirical philosophy have adopted a lot of these terms [Read up on W.V.O. Quine if you enjoy this stuff, because he's fun.], and that's how we start seeing somewhat seemingly-odd usages like this in statistics, which is in very many ways a sort of math-ing of empirical data.

"Correlation does not imply causation" is a favorite refrain of everyone, but sometimes they miss the point. Sometimes correlations are still valuable even when there is no direct causation, but people ignore it because correlation does not imply causation!

Here's a thought experiment. Say there is incontrovertible scientific proof that chewing gum correlates with lowered blood pressure. Upon further study, scientists find that it is the act of moving your jaw that causes the lowered blood pressure, not the gum itself. Person A knows of the correlation, and decides to start chewing gum to lower her blood pressure. Person B comes along and says "Lol don't do that, don't you know that gum doesn't actually lower your blood pressure!" Person B is technically correct, but she essentially "throws the baby out with the bath water", so to speak.

So, it seems that the phrase correlation doesn't imply causation is best evaluated on a case-by-case basis.

It would be wrong to assume drinking diet soda causes obesity because obese people drink it.

It would also be wrong to assume that gum (in my thought experiment) is useless, because it doesn't a direct causative connection to blood pressure reduction. I hear that a lot when people learn that smoking cannabis in moderation improves lung function. "Oh it's not the cannabis that does it, it's the act of inhaling deep." In this case, like my chewing gum example, the causative relationship doesn't matter--the effect is the same either way.

The three genes the authors picked are not the only genes that effect BMI, so factoring them out doesn't completely control for genetic effects. FTO, the gene with the largest effect in their study, only explains 0.34% of variance in BMI. The other genes they used explain 0.15% and 0.10% of variance in BMI. See this study for more details on how these genes were identified).

takes hat off

Thanks for posting the study! It's neat to see this kind of stuff in /r/fitness!

What's interesting to me is that so may of the variants associated with BMI were common in humans. If having a high BMI reduces fitness, selection would presumably keep these variants at pretty low frequencies, so the fact that they're common suggests either that they don't affect fitness or that they're beneficial in some cases.

Caveat: The technique they used, association mapping, is biased towards detecting common things, which is maybe one of the reasons that association mapping hasn't been great at identifying the genes responsible for human diseases -- anything that's rare won't show up as significant.

The thrifty genes hypothesis seems totally reasonable. I'd argue that since many humans are still hungry day to day, 'thrifty genes' are still beneficial today in some cases.

As for hypothesis B, there are some studies starting to do a GWAS where they estimate the variance explained by all the SNPs in their study, not just the ones that were individually significant. One example of this approach is, this study, which was able to explain 45% of variance in human height. Findings like this suggest that a lot of genetic variation is determined by common alleles that have effects too small to be detected by current-sized GWASs. Alternatively, rare alleles with really large effects will also be missed by GWAs and might not even make it into the SNP pools used for these studies, so they could also play an important role in determining trait variation.

And, no need for the undergrad disclaimer! I'm a grad student, so the geneticist hat thing was pretty facetious.

I like this study, but it seems like the editor and, to a lesser extent, the author overestimate the validity of the approach. It's a good step toward eliminating correlative factors, but it isn't exactly causative. It's a common research difficulty, especially in epidemiology, that can get people into a lot of trouble when they try to extrapolate. Causality is almost impossible to establish in retrospective analyses regardless of what statistical or prospective estimation technique you use. This paper is an excellent retrospective analysis that establishes an unconfounded link between BMI and IHD and indicates that higher BMI can contribute to IHD, but without some sort of prospective intervention, it doesn't establish direct causation.

Your TL;DR is accurate: this study effectively claims causation for BMI and heart disease, but it doesn't definitively prove it. I think it would have been more accurate for the editors and authors to state that the three gene loci they studied are unlikely to be the major causative factors in IHD and that their data show that BMI is likely one of the causative factors.

Well, you wouldn't necessarily need a forced intervention. It would need to be a large cohort study, but you could probably rely on the fact that a lot of people tend to get fat. It would take a shitload of controls to do well (and there would still be that ounce of doubt), but with a sufficiently large population and sufficient initial assessments, you could probably make a definitive claim that becoming obese increased your risk of ischemic heart disease by a certain amount. In which case, it would be like a lot of cancer prevention type trials: sign up a huge grab bag of people and then analyze the ones that get the disease using the healthy ones as controls.

But yes, this is good epidemiology, and I wish more epidemiology done by biologists and doctors were this detailed instead of "herpderp we did Wilcoxon on some fat folks!"

This needs to be at the top. I read through the abstract, saw that it's not a longitudinal study, and had a lot of trouble believing that a "causal odds ratio" could definitively say there is a causal link between BMI and IHD.

I imagine there's a pretty strong correlation, but it is important to note the causality since most people conflate the two. People on this subreddit should be well aware that becoming more fit doesn't always involve losing weight (SS and YNDTP, for one).

Is there a difference between 'IDH' and 'IHD' or is that just a series of horrible dyslexic typos by the editor? I was only able to find a description of the 'IHD' acronym in the actual paper. But the explanations at the bottom of the page, including the one you pasted into your post seem to alternate randomly between 'IDH' and 'IHD'...

I also thought there were recent studies showing that being slightly "overweight" correlated with lower incidence of heart disease than being "underweight"? Also that there are plenty of studies showing it's very possible to be "at your target weight" and still have heart disease if you're eating crappy food and not exercising?

This hyperfocus on "being fat" really needs to stop. Eat right, exercise. If you're eating properly and exercising regularly then we don't care what you look like.

Incidentally, being 400lbs is a fairly strong indicator that you are doing neither.

If heart disease follows high BMI, then all the guys in this sub-reddit "bulking up" are putting themselves at risk of heart disease regardless of body fat percentage. I realize that conclusion is not being addressed in this study but it would be good to know more about.

96% of men and 99% of women who were labeled obese by BMI were also considered obese by their body fat percentage according to Romero-Corral, A., Somers, V.K., Sierra-Johnson, J., Thomas, R.J., Bailey, K.R., et al. (2008). Accuracy of body mass index to diagnose obesity in the US adult population. International Journal of Obesity, 32(6), 959-966.

I dare say the people who can squat ~2xBW are likely to be in that 4%.

All the people on this thread seem to be assuming that people with high BMI but low body fat are not at increased risk for heart disease. Has anyone seen a study on this? I have a vague recollection from years ago that the official claim was that high BMI was a risk factor even if you had a normal body fat percentage. Sounds like a difficult study to do so I remain skeptical. Anyway, plenty of people with normal weight, who eat the right stuff and who exercise get heart attacks anyway

This is why the focus on BMI is misplaced. BMI itself is no the issue, it is body fat %. An elevated BMI is associated with disease in populations but useless in measuring an individual's health precisely because BMI cannot distinguish between a pound of muscle and a pound of fat.

Untrue. I'd wager that nearly 100% of athletes would be considered overweight or underweight using BMI, which is a significant amount of people--significant as in that the calculator fails consistently with a certain section of the population.

Penn and Teller's show simply introduced to me the stupidity of the BMI calculator. I've fact checked with other sources to make sure their claims against it were accurate. I'll concede the show is biased (particularly in support of my beliefs), but it does have good information--not all, but most. I linked an article about BMI calculators further down, in one of my buried comments I believe.

96% of men and 99% of women who were labeled obese by BMI were also considered obese by their body fat percentage from Romero-Corral, A., Somers, V.K., Sierra-Johnson, J., Thomas, R.J., Bailey, K.R., et al. (2008). Accuracy of body mass index to diagnose obesity in the US adult population. International Journal of Obesity, 32(6), 959-966.

I'd wager that nearly 100% of athletes would be considered obese using BMI

Average BMIs:

NFL 31.6

NBA 25.1

MLB 26.7

NHL 26.6

which is a significant amount of people.

4,582 according to the rosters in 2010 from those leagues or 0.001% of the population of the US.

I am not part of any athletics, but used to be pretty big into football.

I weigh 230 and, while i do have a little extra, am no where no obese, or even fat. My BMI is 32. I am no longer affiliated with any sports. But it was athletics that caused me to try and get as big as possible.

Trying to say that those 4 organizations have all the athletes ridicules.

Of course not. I mentioned later replying to MadMrha that: "Sure, let's say that .001% is off by two orders of magnitude, that 'athlete' class (which now number 458,200) is .1% of the population. One-tenth of a percent."

We're talking about a very small portion of the population who would be errantly classified as obese by BMI and honestly, if a doctor is dumb enough to call someone who clearly has a low body fat percentage, cares about their fitness enough to maintain a strict diet and exercises obese because of their BMI then no amount of discarding the BMI metric is going to overcome that stupidity.

The numbers from the individual leagues further support the claim that errant BMI classifications aren't that big of a concern:

MLB (93), NBA (5), NFL (1173), NHL (10)

This strongly suggests that if you're very active in a non-football sport, you're likely going to be fine.

BMI is a tool. It ought to be used as such. It is suggestive but not conclusive.

More importantly, the vast majority of people who are going to be harmed by an ill-informed dedication to that metric aren't going to be people classified as obese, it's going to be the 51-64% of people with obese body fat percentages but non-obese BMIs (aka skinnyfat folk and the like).

You're ignoring college athletes, high school athletes, and any casual athlete who doesn't fall within a professional organization. Not to mention, you're containing the search to only a handful of sports. What about boxers, Also, those BMIs you posted of the athletes just supported my case. A BMI of the high 20s is considered overweight by a BMI scale.

Sure, let's say that .001% is off by two orders of magnitude, that 'athlete' class (which now number 458,200) is .1% of the population. One-tenth of a percent.

Also, those BMIs you posted of the athletes just supported my case. A BMI of the high 20s is considered obese by a BMI scale.

Here are the number of pro athletes from those sports with BMIs >29.98:

MLB: 93

NBA: 5

NFL: 1173

NHL: 10

I really don't see how 27.9% of athletes in those pro sports leagues being obese this supports your case that "nearly 100%" of athletes would be considered obese according to BMI.

Look, I get it, BMI is a broad population measure. It's generally used because it's fast and easy (the researchers and your doctor already would be recording height and weight). There do exist people who are unhealthy and have BMIs within the normal range. Only 36% of men and 49% of women had 'obese' bodyfat percentages AND 'obese' BMI numbers in the aforementioned study. But there's no reason to be irrational about the utility of the measure. It has its uses. BMI is more useful than not, especially at the extremes. If you're an athlete with a sub-13 BF% who benches BW, 2xBW squat, has excellent cardio, etc, etc, then I don't see why you'd be remotely worried about your doctor saying "Oh wow, your BMI is a little high". Just look at your body.

Also I think it bears mentioning that just because someone with an obese BMI is an exceptional athlete doesn't necessarily mean that they aren't obese by other measures. Those obese-BMI NFL athletes surely have more muscle mass than most people, but plenty of them carry a lot of extra fat as well.

Absolutely, I didn't want to broach that topic, but IMO those athletes aren't 'healthy'. There is suggestive anecdotal evidence that the worst off, the NFL linemen, do seem to die early, but I'm not aware of anything conclusive.

In any case, we're arguing over the health status of a tiny, tiny fraction of the population. One far too small to significantly dent the utility of BMI, even granting those behemoths are healthy.

I apologize; I've been interchanging the terms obese and overweight, which has caused some confusion. I guess my argument that I'm desperately holding onto here is that it's an imperfect tool, and there are better ways to look at a person's health than by using BMI. Taking various measurements and performing tests are much more beneficial, though I realize they can be more costly. I feel that if one is a medical professional, they shouldn't be using this tool that can't provide consistent results. Ya, I'm not worried about my health though my BMI says otherwise, but I feel that this crappy tool is being used that shouldn't be.

The probability you have an overweight BMI given you're an athlete might be really high. But the probability someone's an athlete given they have an overweight BMI is low. There are just so few athletic people that BMI, on average, is useful.

Here's an example. Let's say the entire population was 1000 people. It's made up of 600 overweight/obese BMI non-athletes, 399 healthy weight people, and a single athlete that has an overweight BMI cuz muscle. Would you really say that BMI isn't useful in this case?

Sure, but you're just one case. Plus, how exactly is "athlete" defined? You certainly are one, but depending on the criteria, you could have a host of other athletes who do fall into normal BMI ranges.

Having said that, I think that BMI should not be used as a sole indicator of health, or at all in certain demographics. But I do think that across a very wide population, where most people are not considered athletes, it works.

I hear this a lot, and yet all of the athletes I know are well within the "normal" BMI range.

Given that was the comment I was replying to, my point is valid.

Having said that, I think that BMI should not be used as a sole indicator of health, or at all in certain demographics. But I do think that across a very wide population, where most people are not considered athletes, it works.

I'm with this guy. I'm not even a powerlifter. Using the BMI calculator, I fall in the 26ish area, and I'm by no means overweight. I'm not deluding myself either. Hard to prove, but take my word for it.

Well, I don't have any data on hand, but I strongly suspect that athletes muscular enough to be obese by BMI standards but not by bodyfat standards represent a very small percentage of the population.

At 6', weighing 225 would make me obese according to BMI, and 25% bodyfat is a commonly-used cutoff for obesity. Certainly there are 6' 225 lb. athletes with <25% bodyfat, but I think if you selected a 6' 225# male from the population at random he would be very likely to be at least 25%. And even among athletes underestimation of bodyfat is quite common.

I don't mean significant as in that it makes up a majority of Americans. I mean that this tool is out there that can't provide consistent and reliable results because a section of the population can prove it wrong most of the time. Why as a professional would you rely on this tool? There are other means.

This comment thread was about obese BMIs, not overweight ones. I never said most people with overweight BMIs are overfat, although at a population level I would still not be surprised if that were true. But it's much more likely that someone will have an overweight BMI due to muscle hypertrophy while still having a normal or low bodyfat percentage than if they had an obese BMI.

This is still an example of correlation is not causation. Without subjecting people to that specific ailment and observing the response (e.g. a manipulative experiment) it always will be.

Doesn't mean that the study isn't cool or show compelling evidence for causation; it's just not causation. Nope, not trolling or playing "arrogant-pretentious-correction-man", I just have to pull the science correction card...cuz..well...I'm a scientist...and we all need more good science. The More you Know.........*

Dude, the title of your post is "Apparently that whole 'Correlation isn't Causation' argument between Heart Disease and BMI may not be a correlation anymore; because science!", so it seems quite clear what you were "trying to get across".

Hi, linguist here: Clinton's request for clarification was, in my opinion, one of the moret astute observations of semantic nuance in recent history. He was absolutely correct to draw attention to the distinctly different uses of 'is' that his accusors were, until that point, successfully conflating.

Briefly, it was a question of aspect - he answered a question about whether 'we were having an affair' (I'm paraphrasing from memory here) and answered 'no' taking it as a question about the current state of affairs, as opposed to a question about what had happened in the past. Aspect is an area where Standard American English is vague - were here could indicate a state in the past or an ongoing state: consider 'we were shopping on the weekend' and 'they were best friends' - the first example is clearly a past event, but the second is ambiguous, and could go either way depending: 'until the scandal, they were best friends' as opposed to 'Dave and Martin were best friends'. 'Bill and Monica were having an affair' is similarly ambiguous - it could refer to a completed affair from the past, which is how the question was presumably meant, but Clinton chose to interpret it as a question about an ongoing, current matter, and answered thusly.

Hence, it's a matter of what the definition of 'is' is.

As a side note, African American Vernacular English has a much more complex copular verb (the copular verb is 'is', many languages omit it entirely) which would have left no room for such ambiguity of aspect. There's a clear distinction between 'they bin fucking' and 'they done been fucking'.

I'm a bit butthurt in retrospect; I don't like it when people imply ulterior motives from a phrase that I merely regurgitated from a source. Its sorta close to putting words in my mouth, which is a pet peeve of mine.

This is not nor has it ever been a personal attack. Why are you so sensitive? You made a shitty post and I criticized your stating (or at least strongly implying) that an elevated BMI "caused" IHD. As a respected member here, you should expect to be held to a high standard.

I never attacked you personally and honestly have no idea why it is you that are so "butthurt". Nice choice of words, btw.

I like how you assumed I am sensitive on the subject matter. My face is rather indifferent.

You attacked my usage of the word 'caused', and I corrected myself when I said 'I meant associated'. I don't see why we are dwelling on this point when I already admitted my fault in word usage.

If you're attacking my choice of words in the Tl;Dr on the basis that I was 'trying to say something', go for it. I really don't care anymore. Nothing I said was incorrect in that part as the authors did claim 'evidence for causation'.

My comments on you being butthurt were based on how you seem to have sent about 20 messages to be based on semantics, and are now attributing some unseen motive to my words by insinuating what I was 'trying to say'.

Ha...well for 50-70 hours a week "I'm on duty". Being careful with what I say and how I say it. But you got me...I was in a rush and I typed with too many ellipses. You win 4 internet points for trying to put down a scientist :P

I see a cruel irony in the public health sector of our nation:
the leading cause of death is heart disease--which obesity is nearing in causation, at least, as a major contributing factor--and we put less and less emphasis on awareness. Programs that focus on reductions of obesity do not even marginally compare in popularity and widespread use as things like breast cancer awareness. What gives? It almost feels like public health is ignoring the glaring problem, the very, very curable illness that is afflicting our country.

What do you mean by the CIs being weak, were they large intervals or was an endpoint close to 0? If the latter, that doesn't really matter, since CIs can't necessarily tell you the strength of association.

Twin 1 does nothing but sit on his ass watching TV, eating Cap'n Crunch out of the box and drinking Coke. Because he's too lazy to go shopping very often he doesn't really over eat. He's 180 pounds but has virtually no muscle and is "skinny fat".

Twin 2 is a power lifter. He eats 4,000 calories a day but he's in the gym 3-4 hours a day. He's got a lot of muscle and fat. He weighs 230 pounds.

Even though Twin 2 has 30 extra pounds of fat he's carrying around his overall fitness level is very high. I have trouble believing he's at a higher risk of heart disease than Twin 1.

I think that it is more accurate to say that an increased BMI is associated with things like diabetes, elevated LDL/HDL ratios and hypertension, all which lead to cardiovascular disease. The key word is associated. An elevated BMI itself does not cause disease. BMI is a very unscientific metric that was never designed to measure individuals (it was designed to measure populations) and using it as a diagnostic tool is fraught with problems. The focus should be on reducing body fat, not BMI.

Correct, but taking the observation about the population and extrapolating it into a prescription for individuals, which is really what it is all about, is wherein lies the rub.

BMI used to measure a person's health status is just bad science. BMI misdiagnoses muscular people on the high end and misdiagnoses about 50% of the people on the low end. Meaning that half the people who are told they have a healthy BMI will actually be obese based on body composition. This is known as normal weight obesity a.k.a. skinny fat.

Bottom line is that an elevated BMI itself does not cause disease, it is elevated body fat that is associated with factors that cause disease.

I'm not sure where you gathered that I, or the authors, were suggesting personalized interventions based on the above information. The authors were suggesting population interventions (which is in accordance with their findings) and I really don't care about interventions right now.

I agree with your statements on BMI in regards to personalized interventions, but that point is irrelevant right now.

I think you are missing my point. In the end any population intervention is accomplished through personal interventions. So, in reality BMI is useless and an elevated BMI does NOT cause disease. If this were the case it would be unhealthy to gain muscle.

Finally, these findings and those of recent, observational studies have important implications for public-health policy because they show that the association between BMI (which is modifiable by lifestyle changes) and IHD is continuous. That is, any increase in BMI increases the risk of IHD; there is no threshold below which a BMI increase has no effect on IDH risk. Thus, public-health policies that aim to reduce BMI by even moderate levels could substantially reduce the occurrence of IDH in populations.

But secondly, I'd argue that population intervention need not be accomplished through personal intervention. Increasing the prevalence of opportunity for exercise (e.g. more bike lanes, more walking paths or parks, encouraging more commercialized growth in non-conventional exercise industries), or restricting the opportunity for over indulgence (e.g. restricting food package size, or other type of food regulations, even so much as extending to restaurants) would be two identifiable ways to reduce societal BMI without being individually intervening.

Your argument was that it would not be possible to intervene on a public level, that intervention was only meant on a personal level. I offered a reasonably supported counterpoint.

If you'd like, I can attack your logic, or lack thereof, and ask rhetorically biased questions as well. I'd support both of my above assertions, but you'd just ignore that as well and claim I'm a some political nazi trying to increase the size of government at the harm of good old citizen Joe. Really? (And this is where, for added effect, I'd imply some kind of eye roll action to emphasize my point, or maybe add another question mark)

Opportunity for rational discussion and reasonable counterpoints doesn't mean shit if people aren't open to new ideas and actually discussing them. It's like some new counter-culture - complain and criticize because it makes me look more mature, analytical, and educated about the issue.

You may think your comments logical and reasonably supported but this is not self-evident.

And yes, you are advocating that the government regulate portion sizes for the "good of the masses". While I have never used the word nazi when referring to you or anyone, as the saying goes, "if the shoe fits..."

You're welcomed to the last word, as I expect all future responses will just be repeating myself. Though I'm amazed at the insinuated personal attack. I suppose I had it coming, huh.

As to your claim of what I'm advocating, it's fallacious. You deemed it not possible to intervene on a public level. I provided two identifiable ways to reduce societal BMI without being individually intervening. At no time did I advocate for either - I simply provided a counterclaim. I'm sorry that you're having trouble distinguishing the difference, and I hope this helps explain, whether it deescalates your responses or not.

It can easily be applied to population based interventions where you cannot micromanage a person's body fat percentage reliably; like a walk-in clinic or large-scale interventions like ad campaigns or governmental grants to weight loss interventions in a town/city.

In regards to your other point, not all interventions are approached the same way as a personalized intervention. If you are trying to target an entire township for weight loss, there is no way in hell you have enough resources to counsel all of them individually.

We are in agreement there, but in the OP you state that BMI causes IHD, which is untrue. While there is indeed a high correlation between elevated BMI and obesity, it is just that, a correlation. Saying that BMI itself is the cause of any disease is just bad science.

Sometimes things are such strong correlations that it is relatively safe to thing of them as similar phenomena. Your bashing of BMI appears that you overestimate the fitness and muscularity of society, or how prominent highly muscular people are.

Of course BMI does not 'cause' IHD, but excess adiposity (using BMI as a biomarker, which is reliable with such a large sample size) is correlated with IHD independent of the most common genetic confounds.

I think you hit the main point here. BMI might not be nearly as reliable as body fat as marker of CVD or IHD, but when you're trying to study such a huge sample size, you're essentially just looking at large numbers of medical records. Height and weight are recorded. Body fat generally is not. It's not perfect, but like you said, in the general context of society, BMI does correlate at least decently well with body fat and provide a widely useable marker.

For the purposes of this thread, assume that my saying 'cause' is always 'associated'. We are talking about survey research here.

And no, I don't believe BMI 'causes' IHD due to the fact that this study cannot come to that conclusion.

I'm just going to rehash my opinion and end this conversation, since we appear to be hopping between semantics, epidemiology, and interventions with no rhyme scheme.

BMI is associated with IHD independent of the three genetic loci that are most commonly associated with BMI and IHD, and this provides some evidence that the correlation between BMI and IHD may be due to the excess state of adiposity per se independent of genes. Further studies should investigate this fact.

You should probably try taking basic statistics. You certainly can find causal relationships without 'direct' experimentation (which I'm assuming means manipulating variables, but that's not true at all either)...I know this as a phd student conducting 'direct' and 'indirect' experiments on a daily basis.

Like a fat guy will see a PSA about the dangers of being fat and suddenly decide he'll eat right and exercise? This is a joke. No sane person will argue that being fat is healthy, it's not like these ad campaigns would help. Just look at the recent gory cigarette ads on the packs.

I didn't read the article (yet) but based on your summary I would conclude the opposite. First you say the Relative Risk was weak and my policy is to ignore factors that don't show large relative risk. I have seen too many such studies fail to be reproduced. Second you indicate that this does not control for other factors such as Diabetes. We all know that obesity increases your chance of getting type II Diabetes. We also know that type II Diabetes causes heart disease. So such a study would only be of interest if it demonstrated what we didn't already know, i.e. Obesity is a significant risk factor for heart disease even if you don't get diabetes or hypertension.

Basically, in looking at cases of Ischemic Heart Disease that co-exist with obesity and then factoring out three common gene variants that could have been to blame, there was still a consistent and positive association with BMI and Heart Disease Risk.

So this study only took into account obese people right? Therefore it can only be applied to people whose BMI is comprised majorly of fat rather than muscle, am I right?

This is a simple thing that anybody with any critical thinking ability should learn after taking a pathophysiology or therapeutics class. I know many of you have not done this, but then again, I don't run about the internet claiming I know shit about physics or engineering when I don't.

did the BMI increase because the subject was eating like shit (resulting in high BMI) or was inactive (resulting in high BMI)... We don't know, both of which could be causes moreso than BMI in and of itself. The study also doesn't seem to imply the general health of the participants, to actually make any inference about causation you would have to study a healthy group and an unhealthy group of similar BMI and compare, as well as active and inactive groups and compare... even then you still haven't proven cause. I guess I am missing how this result is any better than any other non-causal correlation?

I don't think anyone has mentioned this "study." With a sample size of one, the "results" can't say much, but it would be interesting to see what happens with a larger group. Basically, it is the Junk Food Diet:

From the article: "Haub's "bad" cholesterol, or LDL, dropped 20 percent and his "good" cholesterol, or HDL, increased by 20 percent. He reduced the level of triglycerides, which are a form of fat, by 39 percent."

Basically, he ate like crap but the indicators of health improved because he kept his weight down. I'd love to see this done with a larger sample size.

Correlation does not imply causation, but causation does imply correlation.

Also: this is a population study, and not an individual one. On an individual level lowering BMI may or may not induce a lower incidence of heart disease. I'd argue it's difficult to say that it is indeed causation and not correlation until individual studies are done. Cool study though, especially from a public health rather than family care perspective.

Although this does give more truck to policymakers to make population wide health standards for which there are bound to be outliers, eg insurance companies making BMI standards when there are indeed people with high BMIs who are still healthy.

The only thing fat people ever seem to know about BMI is that it has some flaws. "It's an imperfect measure!" they say, while sloppily devouring brownies. Stop feeling judged by metrics and fix your fucking lifestyle.

BMI needs to be updated to account for body fat %, two people can be the same weight and one is desperately unfit, the other, lean and shredded due to difference in muscle mass. case in point, i'm leaner and in better shape now at ~189 than I was a year ago at 180 yet technically i'm at a higher BMI.

I don't understand the link to BMI. BMI does not measure body fat. A muscular, lean individual can have the same BMI as an obese individual. I doubt the person with a high lean body mass is at the same risk for heart disease as someone who is obese.

How the heck do you expect researchers to measure the body fat of over 75,000 people? DEXA scans? Shits expensive and unpractical.

BMI is a reliable and simple way to approximate body fat for large populations. There may be a few people for whom BMI does not accurately reflect their fat and muscle stores, but they are very minimal in regards to an entire population and doesn't really skew the data since their numbers are so small.

As you point out, BMI is an aggregate measurement of body composition. That measurement is not as accurate or useful on an individual basis. A high BMI individual could be obese or well muscled. In our society a high BMI individual is much more likely to be obese than fit but; if you were to limit the scope of the study to only elite lifters, I doubt you would find a casual link between BMI and heart disease.